Single-molecule imaging of transcription dynamics in somatic stem cells

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作者
Justin C. Wheat
Yehonatan Sella
Michael Willcockson
Arthur I. Skoultchi
Aviv Bergman
Robert H. Singer
Ulrich Steidl
机构
[1] Albert Einstein College of Medicine,Department of Cell Biology
[2] Albert Einstein College of Medicine,Ruth L. and David S. Gottesman Institute for Stem Cell Research and Regenerative Medicine
[3] Albert Einstein College of Medicine,Department of Systems and Computational Biology
[4] Albert Einstein College of Medicine,Dominick P. Purpura Department of Neuroscience
[5] Albert Einstein College of Medicine,Department of Pathology
[6] Santa Fe Institute,Department of Anatomy and Structural Biology
[7] Albert Einstein College of Medicine,Gruss
[8] Albert Einstein College of Medicine,Lipper Biophotonics Center
[9] Janelia Research Campus of the HHMI,Department of Medicine (Oncology)
[10] Albert Einstein College of Medicine-Montefiore Medical Center,Albert Einstein Cancer Center
[11] Albert Einstein College of Medicine,undefined
来源
Nature | 2020年 / 583卷
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摘要
Molecular noise is a natural phenomenon that is inherent to all biological systems1,2. How stochastic processes give rise to the robust outcomes that support tissue homeostasis remains unclear. Here we use single-molecule RNA fluorescent in situ hybridization (smFISH) on mouse stem cells derived from haematopoietic tissue to measure the transcription dynamics of three key genes that encode transcription factors: PU.1 (also known as Spi1), Gata1 and Gata2. We find that infrequent, stochastic bursts of transcription result in the co-expression of these antagonistic transcription factors in the majority of haematopoietic stem and progenitor cells. Moreover, by pairing smFISH with time-lapse microscopy and the analysis of pedigrees, we find that although individual stem-cell clones produce descendants that are in transcriptionally related states—akin to a transcriptional priming phenomenon—the underlying transition dynamics between states are best captured by stochastic and reversible models. As such, a stochastic process can produce cellular behaviours that may be incorrectly inferred to have arisen from deterministic dynamics. We propose a model whereby the intrinsic stochasticity of gene expression facilitates, rather than impedes, the concomitant maintenance of transcriptional plasticity and stem cell robustness.
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页码:431 / 436
页数:5
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